Pinned Repositories
MA933-2019
Notebook for Stochastic Modelling and Random Processes module
filterpy
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
ODSC-East2018
"Network/Graph Analysis in Python" repository of 3 hours training session held at ODSC East 2018.
pymc3-kalman
Structural time series using pymc3
stancon18
A primer on Hidden Markov Models using Stan. A Case Study submitted as a candidate for a contributed talk in StanCon 2018. Under review.
torchfilter
Bayesian filters in PyTorch
klbashe's Repositories
klbashe/filterpy
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
klbashe/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
klbashe/ODSC-East2018
"Network/Graph Analysis in Python" repository of 3 hours training session held at ODSC East 2018.
klbashe/pymc3-kalman
Structural time series using pymc3
klbashe/stancon18
A primer on Hidden Markov Models using Stan. A Case Study submitted as a candidate for a contributed talk in StanCon 2018. Under review.
klbashe/torchfilter
Bayesian filters in PyTorch